1. Technical Field
The present invention generally relates to communication networks, such as wireless communication networks, and particularly relates to estimation of channelization code powers for received signal processing.
2. Background
With code-based channelization, e.g., Code Division Multiple Access (CDMA), a received signal represents a composite of individually coded signals. A given individual signal of interest is recovered at the receiver by correlating the received composite signal with the individual signal's spreading code. In general, spreading codes are taken from an orthogonal set of spreading codes, e.g., length-16, length-32, or length-64 Walsh codes. Under ideal reception conditions, the use of orthogonal spreading codes enables the receiver to recover an individual signal of interest from the composite signal that is free from interference caused by the other signals encoded within the composite signal. Of course, for a number of reasons well understood in the art, real-world signal reception and despreading are compromised by a range of signal impairments, including various forms of interference.
As one example of interference arising under practical conditions, real-world wireless communication transmitters commonly transmit signals over dispersive channels. Time dispersion in multipath propagation environments results in at least partial loss of code orthogonality. Orthogonality losses mean that the individual signals are no longer perfectly separated mathematically via correlation processing at the receiver, and the consequent non-zero correlations between the individually coded signals represent a potentially significant source of interference.
As another example, transmissions from adjacent transmitters, e.g., neighboring base stations in a wireless communication network, may use the same spreading codes and therefore interfere with one another. Similar reuse problems arise in Multiple-Input-Multiple-Output (MIMO) transmission scenarios, where channelization code reuse across transmit antennas may be used. As a further example, the use of non-orthogonal (long) scrambling codes between transmitters in wireless communication networks represents an additional source of interference that compromises despreading performance.
Estimating code cross-correlations therefore represents a useful aspect of interference estimation and suppression in CDMA receivers. In turn, estimating the power allocations for channelization codes represents one aspect of determining code correlations. Details relating to certain aspects of code power estimation associated with correlation estimation processing appear in the commonly owned U.S. Pat. No. 7,590,167, which issued on 15 Sep. 2009. The '167 patent is entitled, “A Method and Apparatus for QAM Demodulation in a Generalized RAKE Receiver,” and was filed on 30 Aug. 2005 and assigned application Ser. No. 11/215,584. The '167 patent presents certain aspects of code power estimation as part of “Generalized Rake” (G-Rake) receiver processing, where a correlation fitting procedure was used to estimate code powers.
Further code power estimation information appears in the commonly owned U.S. Pat. No. 7,751,463, which issued on 6 Jul. 2010. The '463 patent is entitled, “Method and Apparatus for Suppressing Interference Based on Channelization Code Power Estimation with Bias Removal,” and was filed on 5 Dec. 2006 and assigned application Ser. No. 11/566,756. Within the context of the '463 patent, Rake-combined values, i.e., the weighted combination of signal samples from plural Rake fingers, provide the basis for estimating code power allocations.
While offering certain advantages at least within specific contexts, it is fair to state that the above examples of known processing approaches to code power estimation do not exploit the potential estimation improvements achievable with the incorporation of joint estimation techniques, nor do they provide a “complete” solution, at least with respect to some processing contexts. For example, certain types of Linear Multi-User-Detection (LMUD) receivers depend on the estimation of received signal amplitudes (for the individual components of a composite signal) and corresponding received signal noise variance, which represents the effect of passing white noise through the received signal digital filtering process.